The Urban Lead Atlas is a collaborative community-based research initiative to create the nations’ first crowd-sourced open online map identifying toxic lead hazards located within the homes, schools, landscape, and lead service lines for water in American cities. The project will begin by integrating data from a small set of cities – New York, Philadelphia, Washington D.C. and Newark - including housing enforcement and lead service line datasets, data on lead dust in schools, and the results of soil lead tests in parks and backyards, on the websites of Columbia University’s Center for Sustainable Urban Development. Ultimately, the goal of the Urban Lead Atlas is to create and populate a fully open online platform that is capable of integrating data from “citizen scientists” and residents regarding the sites of lead hazards in their city’s environment and buildings. This research is important, as experts estimate that over nine million US children have lead blood levels which may cause sub-clinical effects and permanent adverse health, cognitive, and behavior outcomes. The Lead Atlas is intended as the first model for a national effort, the American Lead Atlas project, which seeks to create a national online collaborative map of lead hazards within American cities.

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Locally advanced colorectal cancers that invade adjacent organs (i.e., T4 primary tumors) without evidence of distant metastasis account for approximately 5-15% of new colorectal cancers. There are limited multi-institutional study describing the perioperative complication rates and long-term survival of patients undergoing single organ resection after neoadjuvant chemotherapy and/or radiation versus multivisceral resections for patients with T4 colorectal cancers. Using the American College of Surgeons National Cancer Database (NCDB), we seek to analyze differential outcomes (perioperative complications and overall survival) by procedure performed, tumor details, pathological findings, chemo-radiotherapy regimens, patient demographics.

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Atherosclerosis—a chronic inflammatory disease of the artery wall—is the underlying cause of human coronary heart diseases. Cells within atherosclerotic lesions are heterogeneous and dynamic. Their pathological features have been characterized by histology and flow cytometry and more recently, by bulk-tissue omics profiling. Despite this progress, our knowledge of cell types and their roles in atherogenesis remains incomplete because of masking of differences across cells when using genomic measurement at bulk level. Single-cell RNA sequencing (scRNA-seq) has catalyzed a revolution in understanding of cellular heterogeneity in organ systems and diseases. This project applies scRNA-seq to define the genetic influences on cell subpopulations and functions in atherosclerotic lesion of transgenic mice for candidate risk genes of human coronary heart diseases as inspired by human genomic discoveries. The students involved in this project are expected to work on: (1) analysis of scRNA-seq data using R/Bioconductor packages; (2) Interpretation of the data using pathway and network analysis. Some relevant workflows are available through the “Resources” page of our lab website at https://hanruizhang.github.io/zhanglab/.

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We are interested in investigating how deaths and hospitalizations resulting from opioid overdoses cluster across space and time in the US. This analysis will be conducted with the aid of two comprehensive databases: 1) detailed mortality data across the US; and 2) a stratified sample of all hospitalizations in the US, which can be subset to select for opioid overdoses. Analyses will be extended to drug type (prescription drugs, fentanyl etc.) and subject demographics (age, race, etc.). We have previously conducted similar cluster analysis for other health phenomena.

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Defective efferocytosis, the phagocytic clearance of apoptotic cells, by macrophages is the cause of many human diseases including tumor, autoimmune diseases and atherosclerosis. Enhancing efferocytosis has potential therapeutic benefits. Many key regulators of efferocytosis have been identified, but a systematic approach to map regulators of efferocytosis in an unbiased manner on a genome-wide scale is missing. This project applies innovative genome-wide CRISPR screen to discover novel regulators of macrophage efferocytosis.

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Columbia Data Science Institute (DSI) Scholars Program

The DSI Scholars Program is to engage and support undergraduate and master students in participating data science related research with Columbia faculty. The program’s unique enrichment activities will foster a learning and collaborative community in data science at Columbia.

Columbia University DSI

New York, NY